Cold Outreach logo

Cold Outreach

Community
shawnpang
cold-outreach

When a founder needs to write cold emails or LinkedIn messages to prospects, partners, or investors. Activate when the user mentions cold email, outbound, prospecting, LinkedIn outreach, or needs help getting replies from people who don't know them.

Overview

Publishershawnpang
Repositorystartup-founder-skills
Skill namecold-outreach
Stars
368
Forks
43
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by shawnpang on GitHub. Read the source before you install it.

Installation

Install the Cold Outreach AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/shawnpang/startup-founder-skills/tree/main/skills/cold-outreach
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/shawnpang/startup-founder-skills.git /tmp/startup-founder-skills
mkdir -p .claude/skills
cp -r /tmp/startup-founder-skills/skills/cold-outreach .claude/skills/cold-outreach
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cold Outreach in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cold Outreach on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cold Outreach is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cold Outreach

When to Use

Activate when a founder needs to write cold emails or LinkedIn messages to prospects, potential customers, investors, or strategic contacts. Also use when the user says "nobody replies to my emails," "how do I reach out to X," "write me a cold email," or "help with outbound."

Context Required

From startup-context or the user:

  • Target prospect — Name, role, company, and why them specifically
  • Research signals — Recent news (funding, launches, hires), LinkedIn activity, company growth data, or role/industry context
  • Sender positioning — Who you are, what you offer, your unique credibility
  • Platform — Email, LinkedIn, or both
  • Batch size — Single prospect or multi-prospect campaign

Work with whatever the user provides. A strong research signal and clear value prop is enough to draft. Note what would strengthen the message but do not block on missing inputs.

Workflow

  1. Gather context — Read startup-context if available. Ask for missing info on prospect, value prop, and proof points.
  2. Research the prospect — Conduct web searches for recent signals. The core principle: 10 minutes of research transforms a cold message into a warm one. Rank signals by strength:
    • Tier 1 (strongest): Recent news — funding rounds, product launches, key hires
    • Tier 2: LinkedIn activity — posts, comments, job changes
    • Tier 3: Company growth signals — hiring trends, tech stack changes
    • Tier 4 (weakest): Role/industry awareness only
  3. Assign personalization tier — Based on research signals found:
    • Tier 1 (custom): Named signals across multiple research sources — fully personalized message
    • Tier 2 (templated + personalized): Company info and role context — template with personalized elements
    • Tier 3 (volume template): No signals found — use volume approach with strong value prop
  4. Select mode based on scope:
    • Quick: Single connection request + follow-up for one prospect
    • Standard: Four-touch sequence for a prospect (default)
    • Deep: Multi-prospect system with A/B variant messages
  5. Draft the sequence — Write messages following the structure and rules below.
  6. Self-critique pass — Before delivering, validate that personalization connects to the problem. If you remove the personalized opening and the message still makes sense, the personalization is not working. Rewrite.

Output Format

Deliver all of the following:

  • Connection request (LinkedIn, max 300 characters) or Subject line (email, 2-4 words, lowercase)
  • Primary message — the full outreach text (emails under 125 words, InMails under 500 characters)
  • Follow-up sequence — with timing and a new angle per touch
  • Personalization notes — what to customize per recipient if sending to multiple prospects
  • Tier label — which personalization tier this message uses and why

Frameworks & Best Practices

The Core Principle

The word "cold" is the problem. Every message should feel like it comes from someone who understands the prospect's world. Research is what makes that possible.

Message Structure

  • Connection request (LinkedIn): Max 300 characters. Reference something specific. Never pitch in the request.
  • First message (24-48 hours after connection): "Thanks for connecting" + bridge to a research signal + value statement + question. Keep it conversational.
  • Follow-up 1 (Day 7): Introduce a new angle — different problem, proof point, or insight.
  • Follow-up 2 (Day 14): Share something valuable (article, data, framework) with a soft reconnect.
  • Break-up (Day 21): Professional close — "Closing the loop. If timing is ever right, I'm here."

Writing Principles

  • Write like a peer, not a vendor. Use contractions. If it sounds like marketing copy, rewrite it.
  • Every sentence must earn its place. If it does not move toward a reply, cut it.
  • Lead with their world, not yours. "You/your" should dominate over "I/we."
  • One ask, low friction. Interest-based CTAs ("Worth exploring?") beat meeting requests.
  • Every message must reference a specific research signal or explicitly default to Tier 3. This is a hard rule.

Email Frameworks

  • Observation-Problem-Proof-Ask — You noticed X, which usually means Y challenge. We helped Z with that. Interested?
  • Trigger-Insight-Ask — Congrats on X. That usually creates Y challenge. We have helped similar companies. Curious?
  • Story-Bridge-Ask — [Similar company] had [problem]. They [solved it this way]. Relevant to you?

Subject Lines

  • 2-4 words, lowercase, no punctuation tricks
  • Should look like an internal email ("quick question," "re: [their company]")
  • No product pitches, no urgency, no emojis

What to Avoid

  • Opening with "I hope this finds you well" or "My name is X and I work at Y"
  • Jargon: "synergy," "leverage," "best-in-class," "leading provider"
  • Feature dumps — one proof point beats ten features
  • HTML formatting, images, or multiple links in cold emails
  • Fake "Re:" or "Fwd:" subject lines
  • Asking for 30-minute calls in first touch
  • Sending identical templates with only the name swapped
  • Pitching in a LinkedIn connection request

Founder-Specific Advantages

  • Founder-to-founder or founder-to-exec emails get 2-3x higher reply rates
  • Lead with "I built this because..." — more compelling than "our company offers..."
  • Offer what reps cannot: personal onboarding, product roadmap input, advisory relationships

Related Skills

  • lead-scoring — use to prioritize which prospects to reach out to first
  • sales-script — use when the outreach lands a meeting and you need a discovery call or demo script

Examples

Example prompt: "I need to reach out to VP Engineering at mid-market SaaS companies about our API monitoring tool. We reduced downtime by 73% for Acme Corp."

Good email output (Standard mode, Tier 2):

Subject: api alerts

Hi [Name],

Saw your team just shipped the new payments integration — nice work. Launches like that usually surface a wave of edge-case API failures that are tough to catch with standard monitoring.

We built a tool that catches those failures before customers notice. Acme Corp cut their API downtime by 73% in the first month.

Worth a quick look?

Good LinkedIn connection request:

Hi [Name] — saw the payments launch. We help engineering teams catch API failures before customers do. Would love to connect.

Follow-up (Day 7, new angle):

Hi [Name], quick thought — after launches like yours, the #1 issue teams tell us about isn't downtime, it's the silent failures that slip through alerts. Happy to share what patterns we see across 50+ engineering teams if useful.

Frequently asked questions

What does the Cold Outreach AI skill do?

When a founder needs to write cold emails or LinkedIn messages to prospects, partners, or investors. Activate when the user mentions cold email, outbound, prospecting, LinkedIn outreach, or needs help getting replies from people who don't know them.

Why use Cold Outreach on TypingMind?

Because you install it once and use it with any model. Cold Outreach is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cold Outreach in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/shawnpang/startup-founder-skills/tree/main/skills/cold-outreach. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cold Outreach?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cold Outreach?

As many as you like. As long as a model supports skills, you can use Cold Outreach with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cold Outreach AI skill free?

Yes. It is published on GitHub by shawnpang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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